1. Field of the Invention
The present invention relates to a method for extracting an arterial input function from dynamic medical imaging data, particularly to a method using a blind source separation algorithm to automatically extract an arterial input function closest to the ground-true arterial input function and the application thereof to dynamic contrast enhanced magnetic resonance imaging.
2. Description of the Related Art
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a non-invasive imaging tool for estimation of tissue physiological parameters, such as perfusion, capillary permeability, and the volume of extravascular-extracellular space. The conventional practice of DCE-MRI includes acquiring imaging immediately after contrast agent injection and using a pharmacokinetic model to quantitatively work out some indexes, such as the transfer rate constant (Ktrans) from the intravascular system to the extravascular extracellular space (EES) or vice versa, the distribution volume (Ve) of the contrast agent in EES and the capillary plasma volume (Vp) of the contrast agent in EES, which are very useful in diagnosis and therapeutic estimation of vessel-related diseases, such as tumors and apoplexies.
The pharmacokinetic model requires the knowledge of the arterial input function (AIF). The accuracy of the derived kinetic parameters largely depends on AIF. However, there is still lacking a settled standard to obtain AIF for DCE-MRI. AIF is obtained via manual selection traditionally. However, manual selection is operator-dependent and apparently subjective. Further, the results estimated therefrom are susceptible to the partial volume effect outside the selected region. Parker et al. developed a population-averaged AIF, which is simple and convenient for clinical use. However it neglects individual variation in AIF and may output inaccurate estimation of quantitative parameters. (Refer to Parker G J, Roberts C, Macdonald A, Buonaccorsi G A, Cheung S, Buckley D L, Jackson A, Watson Y, Davies K, Jayson G C. Experimentally-derived functional form for a population-averaged high-temporal-resolution arterial input function for dynamic contrast-enhanced MRI. Magn Reson Med 2006; 56(5): 993-1000.) The reference region approach extracts the AIF by comparing the measured data in healthy tissues with the literature values. It is limited by the requirement of a well-characterized normal tissue within the FOV (Field Of View) and thus still has some problems to overcome.
Accordingly, the present invention proposes a method for extracting AIF and an application thereof to DCE-MRI to overcome the conventional problems and reduce the estimation error caused by the uncertainty of the conventional AIF extraction methods.